HumanRefiner

Introduction

Welcome to the official code repository for the paper "HumanRefiner: Benchmarking Abnormal Human Generation and Refining with Coarse-to-fine Pose-Reversible Guidance."

In this project, we introduce AbHuman, the first large-scale benchmark focused on anatomical anomalies. The benchmark consists of 56K synthesized human images, each annotated with 147K human anomalies in 18 different categories. Based on this, we developed HumanRefiner, a novel plug-and-play method for coarse-to-fine refinement of human anomalies.

Data

Our data is available on 🤗 Hugging Face.

To download the dataset, use the following commands:

git lfs install
git clone https://huggingface.co/datasets/Enderfga/HumanRefiner

After cloning, extract the train and validation datasets:

tar -xzf train.zip
tar -xzf val.zip

Annotation Examples

Below is a detailed illustration of class definitions with visualized examples from the AbHuman dataset:

Cite

If you use our work in your research, please cite our paper:

@misc{fang2024humanrefinerbenchmarkingabnormalhuman,
      title={HumanRefiner: Benchmarking Abnormal Human Generation and Refining with Coarse-to-fine Pose-Reversible Guidance}, 
      author={Guian Fang and Wenbiao Yan and Yuanfan Guo and Jianhua Han and Zutao Jiang and Hang Xu and Shengcai Liao and Xiaodan Liang},
      year={2024},
      eprint={2407.06937},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2407.06937}, 
}

Contact

If you have any questions or suggestions, please contact us:

• Email: enderfga@gmail.com
• GitHub Issues: HumanRefiner Issues

Thank you for your support!